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Gab Post Comments API

Scrape Gab Post Comments data with one API call. Returns the comments on a Gab post, up to 25 a page, in the unified Comment shape under `data.items[]`. Top-level comments and their nested replies come back in one list, in the order Gab's thread view pages them. Every row carries `comment.parent_id`: the post id for a top-level comment, or the parent comment's id for a nested reply, so the tree can be rebuilt. `engagement.likes` is the like count and `engagement.replies` is the reply count. `total` is Gab's own count of replies on the post. Pass `next_cursor` back as `cursor` while it is present. A post that does not exist returns a 404 and is not billed.

Last updated October 2026Maintained by the SocialCrawl team

Lists the comments on a Gab post, 25 a page, with nested replies in the same list and a parent_id on every row so the thread can be rebuilt.

Use it to read the discussion under a Gab post, sorted newest, oldest or top, paging on with next_cursor.

Searching 69 platforms in parallel

·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
Gab API

What can you do with the Post Comments API?

The Post Comments endpoint gives you structured Gab data with computed fields in a single request. No scraping infrastructure to build or maintain.

Example Request

curl -H "x-api-key: YOUR_API_KEY" \
  "https://www.socialcrawl.dev/v1/gab/post/comments?url=https%3A%2F%2Fgab.com%2Fa%2Fposts%2F117445750063805239"
import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/gab/post/comments",
    params={
    'url': 'https://gab.com/a/posts/117445750063805239',
    },
    headers={"x-api-key": "YOUR_API_KEY"},
)

data = response.json()
const response = await fetch(
  "https://www.socialcrawl.dev/v1/gab/post/comments?url=https%3A%2F%2Fgab.com%2Fa%2Fposts%2F117445750063805239",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

Parameters

ParameterRequiredDescription
urlYesGab post URL (`https://gab.com/<handle>/posts/<id>`). A bare numeric post id is accepted too.
cursorNoThe `next_cursor` value from the previous page (a page number), passed back unchanged.
sortNo`newest` (the default), `oldest`, or `top` (Gab's own ranking, which favours the most liked comments). (newest | oldest | top)
sinceNoOnly rows published on or after this date: YYYY-MM-DD (midnight UTC) or an ISO 8601 timestamp. Rows older than it are left off each page. This list is not in date order, so the walk does not stop at the date: keep following `next_cursor`, and each page costs what a page costs even when every row on it is filtered out. A row with no date is kept. `published_after`, `start_date`, `from_date`, `publish_time` (`yesterday`, `this-week`, `this-month`, `last-3-months`, `last-6-months`) and `max_age_days` are accepted and applied as `since`.
untilNoOnly rows published on or before this date: YYYY-MM-DD (that whole UTC day is included) or an ISO 8601 timestamp. Newer rows are left off each page and the walk does not stop, so older pages follow. A row with no date is kept. `published_before`, `end_date` and `to_date` are accepted and applied as `until`.
Example Response

What does the Gab Post Comments API return?

Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.

Example response
{
  "success": true,
  "platform": "youtube",
  "endpoint": "/v1/youtube/video/comments",
  "data": {
    "items": [
      {
        "comment": {
          "id": "Ugzge340dBgB75hWBm54AaABAg",
          "url": null,
          "parent_id": null,
          "post_id": "dQw4w9WgXcQ",
          "text": "Sample comment text (redacted).",
          "author": {
            "username": "user_607bca",
            "display_name": "user_607bca",
            "avatar_url": "https://example.com/avatars/user_b3bde6.png",
            "verified": null
          },
          "engagement": {
            "likes": 322497,
            "replies": 1000
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2025-04-22T19:05:08.000Z",
          "ext": {
            "replies_token": "sc2.eyJzIjoiYSIsImMiOiJVZ3pnZTM0MGRCZ0I3NWhXQm01NEFhQUJBZyJ9",
            "updated_at": "2025-04-22T19:05:08Z",
            "author_channel_id": "user_0faa89",
            "author_url": "https://example.com/user_fa30a8",
            "viewer_rating": "Sample comment text (redacted).",
            "text_original": "Sample comment text (redacted).",
            "preview_replies": [
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg.AHE8_QAWJx9AHE9eIiztxR",
                "channelId": "user_b70959",
                "videoId": "dQw4w9WgXcQ",
                "textDisplay": "Sample comment text (redacted).",
                "textOriginal": "Sample comment text (redacted).",
                "parentId": "Ugzge340dBgB75hWBm54AaABAg",
                "authorDisplayName": "user_a07ce6",
                "authorProfileImageUrl": "https://example.com/avatars/user_b7fd7d.png",
                "authorChannelUrl": "https://example.com/user_7ab559",
                "authorChannelId": {
                  "value": "user_5afaba"
                },
                "canRate": true,
                "viewerRating": "Sample comment text (redacted).",
                "likeCount": 7573,
                "publishedAt": "2025-04-22T19:14:32Z",
                "updatedAt": "2025-04-22T19:14:32Z"
              },
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg.AHE8_QAWJx9AHEAB_-JmDA",
                "channelId": "user_b70959",
                "videoId": "dQw4w9WgXcQ",
                "textDisplay": "Sample comment text (redacted).",
                "textOriginal": "Sample comment text (redacted).",
                "parentId": "Ugzge340dBgB75hWBm54AaABAg",
                "authorDisplayName": "user_d8b3d6",
                "authorProfileImageUrl": "https://example.com/avatars/user_2ece01.png",
                "authorChannelUrl": "https://example.com/user_7a3f35",
                "authorChannelId": {
                  "value": "user_da87da"
                },
                "canRate": true,
                "viewerRating": "Sample comment text (redacted).",
                "likeCount": 3180,
                "publishedAt": "2025-04-22T19:19:13Z",
                "updatedAt": "2025-04-22T19:19:13Z"
              }
            ]
          }
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 3,
              "score_0_1": 0.85,
              "confidence": 0.61
            },
            "question": {
              "p": 0.03
            },
            "purchase_intent": {
              "p": 0.02
            },
            "complaint": {
              "p": 0.04
            }
          }
        }
      },
      {
        "comment": {
          "id": "UgzjClLu_KHsDVWheGx4AaABAg",
          "url": null,
          "parent_id": null,
          "post_id": "dQw4w9WgXcQ",
          "text": "Sample comment text (redacted).",
          "author": {
            "username": "user_f90324",
            "display_name": "user_f90324",
            "avatar_url": "https://example.com/avatars/user_191ddb.png",
            "verified": null
          },
          "engagement": {
            "likes": 1,
            "replies": 0
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2026-10-02T15:39:20.000Z",
          "ext": {
            "replies_token": "sc2.eyJzIjoiYSIsImMiOiJVZ3pqQ2xMdV9LSHNEVldoZUd4NEFhQUJBZyJ9",
            "updated_at": "2026-10-02T15:39:20Z",
            "author_channel_id": "user_121069",
            "author_url": "https://example.com/user_ec3ca5",
            "viewer_rating": "Sample comment text (redacted).",
            "text_original": "Sample comment text (redacted)."
          }
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 3,
              "score_0_1": 0.76,
              "confidence": 0.8
            },
            "question": {
              "p": 0.02
            },
            "purchase_intent": {
              "p": 0.02
            },
            "complaint": {
              "p": 0.03
            }
          }
        }
      }
    ],
    "next_cursor": "sc2.eyJzIjoiYSIsImMiOiJzYzEuZXlKaklqb2lXakpXTUZneU5XeGtNbFo2WkVZNWJXRllTbnBrUXpCMFVUSmtibE5YWkVKVlZscEhUakphVTFRd1NrcFNhMDVPV2pKa1NGRlZSbFJSYkVad1drVnNRMW93U2taYU1WWktZVlZPUWxkVlJrTlRWVnBFVXpKa2JsSXdSa0pWTUVwU1lWVm9TbEZ0WkVKU1YyUldVMWMxY0ZGV2JFSlJhMnhIVVRCc2Nsb3daRUpSVjJ4RldqSTVUbEV3ZEd4YU1UZzFWbFZrUmxNeWF6Rk9SWEJDVWtaV1FsRnNiRUpWVVQwOUlpd2ljeUk2V3lKVlozcG5aVE0wTUdSQ1owSTNOV2hYUW0wMU5FRmhRVUpCWnlJc0lsVm5lbXBEYkV4MVgwdEljMFJXVjJobFIzZzBRV0ZCUWtGbklsMTkifQ",
    "total": null,
    "labels": {
      "presets": [
        "sentiment",
        "question"
      ],
      "rows": 2,
      "labelled": 2,
      "cached": 1,
      "skipped": 0,
      "unjudged": 0,
      "dropped": 0,
      "dropped_ids": [],
      "extra_credits": 0,
      "methodology_version": "labels/1",
      "mode": "default",
      "status": "complete",
      "pending": 0,
      "pending_ids": []
    },
    "label_share": {
      "policy_version": "share/1",
      "presets": {
        "question": {
          "n": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "purchase_intent": {
          "n": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "complaint": {
          "n": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "sentiment": {
          "positive": {
            "n": 2,
            "counted": 2,
            "abstained": 0,
            "share": null,
            "low": 0.425,
            "high": 1,
            "receipts": [
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg",
                "text": "Sample comment text (redacted)."
              },
              {
                "id": "UgzjClLu_KHsDVWheGx4AaABAg",
                "text": "Sample comment text (redacted)."
              }
            ],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 2,
            "nulls": 0,
            "low_confidence": 0
          },
          "neutral": {
            "n": 2,
            "counted": 0,
            "abstained": 0,
            "share": null,
            "low": 0,
            "high": 0.575,
            "receipts": [],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 0,
            "nulls": 0,
            "low_confidence": 0
          },
          "negative": {
            "n": 2,
            "counted": 0,
            "abstained": 0,
            "share": null,
            "low": 0,
            "high": 0.575,
            "receipts": [],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 0,
            "nulls": 0,
            "low_confidence": 0
          }
        }
      }
    },
    "comment_language": {
      "policy_version": "share/1",
      "n": 2,
      "abstained": 0,
      "judged_by": {
        "script": 0,
        "choice": 2
      },
      "shares": {
        "en": {
          "n": 2,
          "counted": 2,
          "abstained": 0,
          "share": null,
          "low": 0.425,
          "high": 1,
          "receipts": [
            {
              "id": "Ugzge340dBgB75hWBm54AaABAg",
              "text": "Sample comment text (redacted)."
            },
            {
              "id": "UgzjClLu_KHsDVWheGx4AaABAg",
              "text": "Sample comment text (redacted)."
            }
          ],
          "policy_version": "share/1",
          "too_few": true
        }
      }
    },
    "comment_recency": {
      "policy_version": "d09-1",
      "n": 2,
      "counted": 2,
      "abstained": 0,
      "share_last_24h": 0.5,
      "share_later_half": null,
      "too_few": true,
      "stage": "unknown",
      "order": "top",
      "recent_share_is_floor": true,
      "receipts": [
        {
          "id": "UgzjClLu_KHsDVWheGx4AaABAg",
          "text": "Sample comment text (redacted)."
        }
      ]
    },
    "dropped": 0
  },
  "credits_used": 1,
  "credits_remaining": 9999,
  "request_id": "req-8Kq2ZmR4vT9xLb3P",
  "cached": false,
  "pagination": {
    "next_cursor": "sc.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",
    "has_more": true,
    "page_size": 2
  },
  "redacted": true
}

Example captured from the YouTube API. Every SocialCrawl endpoint returns this same unified schema, so your Gab Post Comments response has the same fields.

API Details

How does the Gab Post Comments API work?

Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.

Method

GET

Response

JSON

Why SocialCrawl

Why use SocialCrawl for Gab Post Comments data?

We handle the complexity of Gab data extraction so you can focus on building. Unified schema, AI enrichment, and zero platform logic in your code.

Developer First

How do you scrape social media data in seconds?

The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 69 platforms covering 10B+ monthly active users.

One schema, every platform

Query 69 platforms with identical response structures. Write your integration once.

Computed fields, not just scraped

When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language. Ready to use.

See your data before you code

Visual Data Explorer. Paste any URL, get rich result cards, sortable tables, CSV export.

import requests

response = requests.get(
    'https://www.socialcrawl.dev/v1/tiktok/profile',
    params={'handle': 'charlidamelio'},
    headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json()
[ .JSON ]
{
  "success": true,
  "platform": "tiktok",
  "data": {
    "author": {
      "username": "charlidamelio",
      "followers": 152400000
    },
    "engagement": {
      "likes": 12400000000,
      "engagement_rate": 0.087
    },
    "metadata": {
      "language": "en",
      "content_category": "lifestyle"
    }
  }
}
+ 69 platforms

Ready to scrape Gab Post Comments data?

Get your API key and start pulling Gab data in under 60 seconds.

Start for free

🤖 AI agent or LLM? Read this page as markdown